Morpho-agronomic variability of okra [Abelmoschus esculentus (L.) Moench] genotypes in Dire Dawa, eastern Ethiopia

A total of 21 okra genotypes were evaluated for 25 morpho-agronomic traits in 2020 at Dire Dawa, Ethiopia in a randomized complete block design with three replications. Analysis of variance showed significant differences at p<0.05 level of significance for all traits. Estimates of genotypic (GCV) and phenotypic (PCV) coefficients of variation range from 9.16 to 42.3% and 9.33 to 44.16%, respectively. Heritability in a broad sense (H2) and genetic advance as a percent of the mean (GAM) ranged from 29.57 to 91.89% and 10.39 to 83.53%, respectively. Estimated variability components (GCV, PCV, H2, and GAM) were high and moderate for all traits except days to 50% emergence 9.33% of GCV and PCV, internode length 9.16% of GCV and green fruit width 29.57% of H2 that were categorized under low. The first four principal component axes (PCA1 to PCA4) accounted for 7.83 to 35.02%, which accounted 74.56% of the total variability with eigenvalues that ranged from 1.95 to 8.75. Genetic distances estimated by Euclidean distance from the 25 traits ranged from 2.33 to 12.56 with a mean of 6.83, standard deviation of 1.8, and a coefficient of variation of 26.46%. The genotypes were grouped into four distinct clusters using the Euclidean distance matrix using UPGMA. Indigenous okra genotypes collected from Ethiopia were more divergent with high genetic distances and had a higher performance for most of the traits including growth, green fruit yield, and seed yield than introduced genotypes. In conclusion, this study showed the presence of variation among genotypes for most of the traits, indicating that selection of genotypes could be effective to develop okra varieties with high green fruit and seed yield through direct selection or crossing.


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The data underlying the results presented in the study are available from (include the name of the third party • All relevant data are within the manuscript and its Supporting Information files. and contact information or URL Okra is mainly grown for its immature pods that are consumed as a fresh vegetable, a snack, a 78 5 and (Bamaya-Humera) collected from northern Ethiopia. Two (SOH 714 and SOH 701)  141   introduced and registered commercial varieties by companies, seven commercial varieties  142   introduced from India and one commercial variety introduced from USA for research purposes  143 were used for the study (Table 1). 144 The field experiment was conducted in a randomized complete block design with three 145 replications. Each genotype was randomly assigned to a plot in each replication in the experimental 146 field. Each plot consisted of 12 plants at a spacing of 0.6 m between plants. The spacing between 147 the plots and adjacent replications was 0.8 and 2 m, respectively. Three seeds per hill was sown 148 and thinned to one plant per hill when plants reached 3-4 leaf stages. 149 Land preparation was done in the first week of February 2020 using a tractor and human labour. 157 The soil was levelled to permit furrow irrigation every five days. The rows were raised to increase 158 soil surface area, aeration, and drainage. The ridges were made according to the plant spacing's by 159 hand. Okra seeds were sown in mid-February 2020 and placed at the depth of 5 cm. Furrow 160 irrigation was applied every five days. Cultural practices such as cultivation, hoeing, weeding, and 161 earthing-up were applied uniformly. Green fruits were harvested every five days from 10 plants in 162 the middle row to estimate green fruit yield and related traits and dry pods (green colour of pods 163 changed to grey colour) from two plants at both ends of the row were harvested to collect seed 164 yield and seed yield related data. 165 The quantitative data was subjected to analysis of variance (ANOVA). The data recorded as 253 percentage were transformed before subjecting to analysis of variance (Gomez and Gomez, 1984). 254

Data Collection
The comparison of mean performance of genotypes was conducted following the significance of 255 mean squares using the least significant difference at 5% probability level. The trait that exhibited 256 significant mean squares in general ANOVA was further subjected to genetic analyses as a 257 description given in the subsequent subtitle. Descriptive statistics were used to describe qualitative 258 data. 259

Phenotypic and Genotypic Variability 260 261
The variability was estimated by genotypic and phenotypic variances and coefficient of variation. 262 The genotypic and phenotypic variance were estimated as proposed by ( Where,X ̅ = population mean. 294 11

Principal Component Analysis 295
The morpho-agronomic traits that exhibited significant mean squares in general ANOVA were 296 pre-standardized to means of zero and variance of unity before principal component analysis (PCA) 297 was performed to avoid bias due to differences in measurement scales (Manly, 1986). After 298 standardization, the data were subjected to principal component (PC) analysis to understand which 299 trait(s) much contributed to the divergence or total variability of genotypes. 300

Genetic Distance and Clustering 301
The morpho-agronomic traits that exhibited significant mean squares in general ANOVA were 302 used to estimate genetic distances and clustering of genotypes. Genetic distances of 21 okra 303 genotypes were estimated using Euclidean distance (ED) calculated from quantitative traits after 304 standardization (subtracting the mean value and dividing it by the standard deviation) as 305 established by reference (Sneath, 1979)  Where; EDjk = distance between genotypes j and k; xij and xik = phenotype trait values of the 308 i th character for genotypes j and k, respectively; and n = number of phenotype traits used to 309 calculate the distance. The distance matrices of phenotype traits were used to construct a 310 dendrogram based on the Un-weighted Pair-group Method with Arithmetic Means (UPGMA). 311 The results of cluster analysis were presented in the form of a dendrogram. In addition, the 312 mean ED was calculated for each genotype by averaging of a particular genotype with the other 313 20 genotypes. The calculated average distance (ED) was used to estimate which genotype(s) is 314 closest or distant to others. 315  The results of analysis of variance of 21 okra genotypes for crop phenology and growth traits 320 showed significant difference. The results indicated that the presence of significant variations 321 among genotypes for crop phenology and growth traits might be given a good opportunity for 12 breeders to select genotypes with varied crop maturity and better growth performance. (Mihretu,323 Weyessa and Adugna, 2014) and (Muluken, Wassu and Endale, 2016) reported the presence of 324 highly significant differences among okra genotypes for crop phenology (days to 50% emergence, 325 50% flowering, and days to maturity) and growth traits (number of branches and internode length). 326

RESULTS AND DISCUSSION
The okra genotypes were collected from south-western, north-western and western parts of 327 Ethiopia. 328

Green Fruit Yield and Yield Components 329
The results of analysis of variance of 21 okra genotypes for number of green fruits, weight of green 330 fruit per plant, green fruit length, average green fruits weight, green fruit width and fruit yield per 331 hectare showed significant difference. The results indicated that the presence of significant 332 differences among okra genotypes for green fruit yield and yield component traits might be given 333 a good opportunity for breeders to select high yielding and most preferable genotypes. 334 (Mohammed, Bekele and Kumar, 2017) reported the presence of significant differences in the 335 number of fruits per plant, green fruit weight, fruit length, and fruit width. 336

Dry Pod, Seed Characteristics and Seed Yield 337 338
The genotypes exhibited significant differences for number of dry pods, weight of dry pods per 339 plant, average dry pod weight, number of seeds per pod, hundred seeds weight, seed moisture 340 content, seed weight per pod and seed yield per plant. The results indicated that the presence of 341 significant differences among okra genotypes for seed yield and related traits will help breeders 342 for hybridization/ selection of traits of interest. (  The recently released variety 23793 (Bamaya Humera) and other genotypes collected from 350 northern Ethiopia (Humera 01) were earlier to attain 50% emergence (9.33 days) followed by the 351 two registered commercial varieties (SOH 701 and SOH 714) 9.66 days. The two registered 352 13 commercial varieties (SOH 701 and SOH 714) also had mean days to 1 st flowering (54.65days), 353 50% flowering (69.85days) and days to maturity (83.85days). The two genotypes (Bamaya 354

Mean Performance of Okra Genotypes
Humera and Humera 01) collected from northern Ethiopia also had 46.5, 55.35, and 67 mean days 355 to 50% emergence, days to 1 st flowering and days to maturity, respectively. The seven genotypes 356 (Dhenu, Kiran, Kraft, Pocha, Mithra, ArkaAnamica, and NamdHari) introduced from India also 357 showed early mean days to 1 st flowering (46.98), days to 50% flowering (55.47days) and days to 358 maturity (66.64). Genotypes collected from north-western Ethiopia (240209 and 240207) also 359 showed days to 50% emergence (11.67 days), 1 st flowering (58 days), 50% flowering (74.5 days) 360 and days to maturity (92.33 days). Likewise, genotypes collected from south-western Ethiopia 361 (240586, 240609, and 240591) had mean days to 50% emergence of (11.11days), 1 st flowering 362 (60), 50% flowering (69.56) and days to maturity (84.46). 363 The genotype introduced from USA (Clemson Spineless) also showed mean days to 50% 364 emergence of (12), 1 st flowering (53.3), 50% flowering (62.3), and days to maturity (78.3). 365 Genotypes collected from western Ethiopia (242443, 92203, 245157, and 242433) showed lately 366 mean 11, 59.75, 75.91and 96.5 days to attain 50% emergence, 1 st and 50% flowering and days to 367 maturity, respectively ( Table 2). The genotypes showed wide range of variations for phonological 368 traits. Okra genotypes were introduced from other countries and the two commercial varieties were 369 early 1 st and 50% flowering and days to maturity than okra genotypes collected from Ethiopia. 370 This earliness might be an advantage in areas where the rainy season is short and the producer 371 might help in capturing early market which fetches high price in markets and earn high income by 372 supplying fruit early where fruits are not harvested from other genotypes under irrigated 373 production. The research results suggested the higher chance of developing okra varieties for better 374 growth, green fruit yield, and other desirable traits either through selection, breeding, and/or 375 crossing of genotypes. 376 (Temam, Mohamed and Aklilu, 2020) reported significant variations for days to 50% emergence 377 (7.5 to 11 days), days to first flowering (44.5 to 71 days), days to 50% flowering (48.5 to 77.5 378 days) and days to maturity (75.5 to 104.5 days). He also reported genotypes collected from western 379 Ethiopia (Benishangul Gumuz) had mean performance greater than the mean values of the three 380 tested genotypes for days to emergence.     (Table 3). 503 20 The current study result indicates that there is a wide variation in green fruit yield and yield 507 component traits of okra genotypes collected from different parts of Ethiopia and introduced to 508 other countries, which is a key solution to the current climate change concern (Binalfew and 509

Green Fruit Yield and Yield Components
Alemu, 2016). Most of the genotypes collected from south-western, north-western, northern, and 510 western Ethiopia had higher mean performance of green fruits yield and yield components than 511 the introduced and two registered commercial varieties. This showed that there is wide variability 512 in green fruit yield and yield components in Ethiopia through collection and selection of okra south western Ethiopia showed the highest mean values of hundred seed weight 6.33 and 6.91g, 542 respectively. While the remaining groups of genotypes collected from northern Ethiopia, 543 introduced from USA (Clemson Spineless), the two registered commercial varieties, genotypes 544 collected from north western Ethiopia and introduced from India showed the lowest mean values 545 of hundred seed weight 3.46, 5.8, 6.06, 6.24 and 6.26g, respectively (Table 4). The current result 546 indicate that the highest number of seeds and hundred seed weight were considered as selection 547 criteria for the breeding of okra genotypes for seed yield and yield component traits (Gerrano, 548 2018). 549 Genotypes collected from northern Ethiopia (Bamaya Humera and Humera 01), 7.17% had the 550 lowest mean values of seed moisture content, while the remaining group of genotypes collected 551 from north western (240209 and 240207), western Ethiopia (242443, 9220, 245157 and 242433), 552 two registered commercial varieties (SOH 701 and SOH 714) and introduced from USA (Clemson 553 Spineless) had higher seed moisture content from 9.4 to 11.42%. Moisture content is an index of 554 23 its water activity important for stability in seeds. Low moisture content in the seed is important to 555 extend the shelf-life of okra seeds in storage place since selecting genotypes that had low seed 556 moisture content is one of the climate smart post-harvest handling technology to save farmer's 557 economic loss. Genotypes introduced from USA (5168.9mg), two registered commercial verities 558 (5386.9mg), genotypes collected from western (6005.3mg), north western (6045.9mg) and south 559 western Ethiopia (6483.56mg) had highest mean values of seed weight per pod without non 560 significance difference among them, while the remaining group genotypes collected from northern 561 (Bamaya-Humera and Humera 01) and introduced from India showed lower mean of seed weight 562 per pod 2032.5 and 4580.47mg, respectively. genotypes collected from south-western Ethiopia 563 (60.66g), the two registered commercial verities (61.30g) and genotypes collected from northern-564 The observed high number of dry pods, number of seeds per pod, and hundred seed weight in okra 580 genotypes suggested that the higher chance of improving seed yield of okra to produce high 581 amount of edible oil per unit area. The oil content of the seed is quite high at about 40% and the 582 seeds are also used as a substitute for coffee (Mohammed et al., 2022).

Estimates of broad sense heritability 655
Estimates of heritability in broad sense (H 2 ) for 25 quantitative traits of okra genotypes are 656 presented in table 5. The heritability values in the broad sense ranged from 29.57 to 91.89%. 657 According to (Johnson, Robinson and Comstock, 1955)), heritability is categorized as low (0-658 30%), moderate (31-60%), and high > 60%. Based on this classification, all phenological traits 659 (days to 50% emergence, 1 st and 50% flowering, and days to maturity), growth traits (stem 660 diameter, number of internodes, internode length, leaf length and width), and seed moisture content 661 28 fall under the moderate heritability category (31-60%), while the other traits, plant height, number 662 of branches per plant, number of green fruits, weight of green fruits, green fruit length, average 663 fruit weight, fruit yield per hectare, number of dry pods, weight of dry pods, average dry pod 664 weight, number of seeds pod, hundred seed weight, seed weight per pod and seed yield per plant 665 under high heritability category value (>60%). Green fruit width had also low H 2 (<30%). 666 The current study result indicates that most of the traits (14 out of 25) had high values of 667 heritability, which is important for future okra improvement programs for green fruit, seed yield 668 and related traits. It is important to apply some backcross to concentrate these characters in 669 genotypes because a lot of traits appear to be controlled by genes with additive effects. Heritability 670 is a good index of the degree of transmission of the characters from parents to their offspring 671 (Komal et al., 2022). The consistency in the performance of progeny in succeeding generations 672 depends mainly on the magnitude of the heritable portion of the variation. Heritability indicates 673 the possibility and extent to which improvement can be brought about through selection and it may 674 be of broad and narrow senses (Robinson, 1966).

Estimates of genetic advance 689
In this study, genetic advance percent mean (GAM) ranged between 10.39 to 83.53%. Genetic 690 advance as percent mean (GAM) was categorized as low (0-10%), moderate (10-20%) and high 691 29 (≥20%) (Johnson, Robinson and Comstock, 1955). Accordingly, high GAM values were estimated 692 for days to maturity, plant height, all green fruit characters except green fruit width, and all seed 693 yield and related traits. Moderate GAM values were estimated for phenological traits (days to 50% 694 emergence, 1 st and 50% of flowering), and growth traits, stem diameter, number of internodes, 695 internodes length, leaf length and width and green fruit width (Table 5). 696 PCV=phenotypic coefficient of variation, GCV=Genotypic coefficient of variation, 700 H 2 =Heritability in broad sense, GA=Genetic advance, GAM=Genetic advance as percent of mean. 701 High genetic advance as a percent of mean indicates the traits are controlled by additive genes 702 (Panse and Sukhatme, 1957). Heritability estimates along with genetic advances were more useful 703 in predicting the effect of selecting the best individuals (Johnson, Robinson and Comstock, 1955). 704 30 It provides better information than each parameter alone and an expression of additive gene action 705 (Das et al., 2012). 706 (Temam, Mohamed and Aklilu, 2020) reported GAM values that ranged from 9.16 to 109.14 % in 707 which high genetic advance was observed for all studied traits except days to maturity which had 708 moderate GAM and low for hundred seed weight. (  Biplot analysis was carried out based on the first two PCAs (Figure 1). The genotypes and 768 quantitative traits were shown on a biplot to visualize their associations and differences. The first 769 and second PCAs biplot explained 55.56% of the total variability among the genotypes displaying 770 days to first flowering, days to 50 % flowering, days to maturity, number of internodes, internode 771 length, stem diameter and green fruit length being considered as the most discriminating traits. 772 The genotypes that were positioned on the left top quadrant were associated and characterized by 773 the tallest green fruit width (GFW), highest weight of green fruit (WGFPP), average green fruit 774 weight (AGF) and green fruit yield (FYD). The genotypes demarcated on the right top quadrant 775  According to the mean analysis of clusters, selection of genotypes from Clusters I and III is 912 possible to obtain genotypes with the highest green fruits yield and other desirable traits. It is 913 suggested also to make crosses between the two cluster members and genotypes from Cluster I to 914 combine desirable traits in hybrids and searching better performing varieties in subsequent